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memory GMRES preconditioner



Dear all,

I think that the GMRES ILU(p) preconditioner in my program is consuming too much memory. I just would like to check if it is correct or not and compare this experience with other PETSc users.
For a quite small sparse matrix (dimension = 3500 and 2.5 Mb) the memory consumed while the preconditioner is created is more or less:

ILU                                 level approximate increase of memory waste (Mb)

4                                       9
8                                       26
12                                     43
16                                     53
20                                     68

Moreover a fast convergence is reached suddenly (i.e. for ILU level 25 convergence is not reached after 3000 iterations but for ILU level 30 the convergence is reached in 7 iterations).
I suppose that some of the problems are caused by the large condition number of the matrix but in any case I guess that the memory used by the preconditioner is too large.
I have tried to improve the performance using: PCFactorSetFill, PCFactorSetAllowDiagonalFill and PCFactorSetUseDropTolerance but I have not succeed.

I would also like to know how to estimate a priori the memory required for a PETSc sparse matrix if the non null entries are known. Is the following rule: 1 double/complex<double> and 2 integers per non null coefficient, a good approximation (taking into account PETSc implementation)? Is the same rule valid for the case of the preconditioner?

I will give some details on the particular situation being solved:
------------------------------------------------------------------------------------------------------------

Type of matrix: FEM resolution of an structural dynamic problem

(K + w*w*M) | L^T

------------------------- = System matrix

L                    | 0


K == stiffness matrix (square banded)
M == consistent mass matrix (square banded, and same nonzero pattern than K)
w == pulsation of the problem (scalar)
L == Lagrange multipliers matrix (rectangular sparse)

The matrix is in general ill conditioned and non positive definite.

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And my use of PETSc functions is as follows:

ierr = KSPCreate(PETSC_COMM_WORLD,&MyKsp);CHKERRQ(ierr);

ierr = KSPSetType(MyKsp, KSPGMRES);CHKERRQ(ierr);

ierr = KSPSetOperators(MyKsp,MyMat,MyMat,DIFFERENT_NONZERO_PATTERN); CHKERRQ(ierr);


ierr = KSPGetPC(MyKsp,&(MyPc));CHKERRQ(ierr);

ierr = PCSetType(MyPc,PCILU);CHKERRQ(ierr);

ierr = PCFactorSetLevels(MyPc, LevelNumber);CHKERRQ(ierr);


PetscReal realshift = 1.0;

ierr = PCFactorSetShiftNonzero(MyPc, realshift); CHKERRQ(ierr); //With and without this line


ierr = KSPSetTolerances(MyKsp,tol,PETSC_DEFAULT,PETSC_DEFAULT,itmax);CHKERRQ(ierr);

ierr = KSPSetInitialGuessNonzero(MyKsp,PETSC_TRUE);CHKERRQ(ierr);


ierr = KSPGMRESSetRestart(MyKsp, max_steps_restart); CHKERRQ(ierr); //With and without this line


ierr = KSPSetFromOptions(MyKsp);CHKERRQ(ierr);

ierr = KSPSolve(MyKsp,MyVector,x);CHKERRQ(ierr);

-----------------------------------------------------------------------------------------------------------

Thank you very much in advance,


Jordi Poblet Puig